Optical Flow Image Analysis of Emotional Human Facial Expressions – Forensic Applications

Sztynda, T; Chow, D; Lal, S

Optical Flow Image Analysis of Emotional Human Facial Expressions – Forensic Applications

Sztynda, T

Chow, D Lal, S

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Publisher:: Coimbatore Institute of Information Technology
Publication Type:: Journal Article
Citation:: International Journal of Artificial Intelligence Systems and Machine Learning, 2020, 11, (12), pp. 209-218
Issue Date:: 2020-01-09

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Field	Value	Language
dc.contributor.author	Sztynda, T https://orcid.org/0000-0002-8957-0864
dc.contributor.author	Chow, D
dc.contributor.author	Lal, S https://orcid.org/0000-0002-0911-0850
dc.date.accessioned	2021-04-28T03:12:45Z
dc.date.available	2019-12-20
dc.date.available	2021-04-28T03:12:45Z
dc.date.issued	2020-01-09
dc.identifier.citation	International Journal of Artificial Intelligence Systems and Machine Learning, 2020, 11, (12), pp. 209-218
dc.identifier.issn	0974-9543
dc.identifier.uri	http://hdl.handle.net/10453/148448
dc.description.abstract	Emotional facial expressions have been suggested as indicators of a person’s intended actions when they display a set of specific facial reactions. Our aim was to investigate Optical Flow to identify specific emotions with the long-term objective to create an algorithm that would automate the process. This would remove all allegations of bias to give security personnel an objective way of screening individuals in a crowd who may require closer scrutiny. This paper describes our preliminary studies, using film clips to elicit dynamic natural facial responses. This has identified key elements that need to be evaluated further, such as gender and age of the people under observation, as well as specific facial elements that may be of greater benefit than whole facial images for the purpose of screening crowds for potential perpertrators of anti-social behaviour.
dc.language	en
dc.publisher	Coimbatore Institute of Information Technology
dc.relation.ispartof	International Journal of Artificial Intelligence Systems and Machine Learning
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Optical Flow Image Analysis of Emotional Human Facial Expressions – Forensic Applications
dc.type	Journal Article
utslib.citation.volume	11
utslib.location.activity	Australia
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
pubs.consider-herdc	true
dc.date.updated	2021-04-28T03:12:44Z
pubs.issue	12
pubs.publication-status	Published
pubs.volume	11
utslib.citation.issue	12

Abstract:

Emotional facial expressions have been suggested as indicators of a person’s intended actions when they display a set of specific facial reactions. Our aim was to investigate Optical Flow to identify specific emotions with the long-term objective to create an algorithm that would automate the process. This would remove all allegations of bias to give security personnel an objective way of screening individuals in a crowd who may require closer scrutiny. This paper describes our preliminary studies, using film clips to elicit dynamic natural facial responses. This has identified key elements that need to be evaluated further, such as gender and age of the people under observation, as well as specific facial elements that may be of greater benefit than whole facial images for the purpose of screening crowds for potential perpertrators of anti-social behaviour.

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http://hdl.handle.net/10453/148448